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Configure Box Plots

Box Plots allow you to quickly compare distributions among groups of data or data sets. This article shows you how to configure Box Plots in Visual KPI Designer. Users can also configure Box Plots ad-hoc in Visual KPI sites.

You can configure Box Plots to show the statistical distribution of data, and as always in Visual KPI, the data can be viewed over time. For example, in a series of temperatures over a specified time, you could quickly see the lowest, highest and median temperature, as well as the median temperature in the upper and lower quartiles.

Visual KPI Box Plots

In Visual KPI sites, hover over Box Plots to see the distributed values. You can configure Box Plots based on time-series or non-time-series data. You can also configure Box Plots manually, or you can configure query-based Box Plots.

There are four ways to render Box Plots in Visual KPI:

  • KPI-based Box Plots (created ad-hoc in Visual KPI sites)
  • Managed Box Plots (defined Pens)
  • Query-based Box Plots (pre-calculated stats)
  • Query-based Box Plots (raw data)

Managed and query-based Box Plots are configured in Visual KPI Designer.

Define Box Plots Attributes

To configure Box Plots in Visual KPI Designer, create a new chart and then define attributes. Box Plots are found under Charts in Visual KPI Designer (see Create & Configure Charts).

After you have created and configured some basic attributes for a Box Plot, such as the name, description and display order, you can begin to describe the data that will build the Box Plots. Here, we show you the basic attributes that you need to set in order design a basic Box Plot. To see all of the possible attributes you can configure, see Charts Attributes & Keywords Reference Guide.

Configure Box Plot Values and/or Interfaces

To add data to your Box Plots, you add a value, calculation and/or interface for each box. You can also add Connect Strings.

You can select the color for each box, or leave the attribute blank and Visual KPI will assign a default color. The bars may not have varied colors, but may be all the same color. Bar colors can also be read from a database.

Query-based Box Plots (pre-calculated stats)

The query or stored procedure can either take in no date (static), a timestamp (point in time with scroll interval), or a start and end timestamp (range-based).

The query must return the following fields (names are important):

  • Required: Min, Q1, Median, Q3 and Max
  • Optional: Name and Color (hex).

Example Query Result:

Name Color Min Q1 Median Q3 Max
Unit A #222999 5.6 22 50.3 61 96.2
Unit B #445ba3 2 12 52 62 102
Unit C #222999 1 11 51 61 101
Unit D #445ba3 2 12 52 62 102
Unit E #222999 1 11 51 61 101

Query-based Box Plots (raw data)

The query or stored procedure can either take in no date (static), a timestamp (point in time with scroll interval) or a start and end timestamp (range-based).

Note: If you have a lot of data, raw data query-based Box Plots will perform more slowly. It may be better to calculate the stats in your database and let Visual KPI read the stats.

The query must return the following fields (names are important):

  • Required: Name, Value
  • Optional: Color (hex).

Example Query Result:

Name Color Value
Tank 100 #ff0000 2.518743
Tank 100 #ff0000 36.04321
Tank 100 #ff0000 36.04899
Tank 100 #ff0000 4.524793
Tank 100 #ff0000 30.03399
Tank 100 #ff0000 75.10507
Tank 100 #ff0000 16.27936
Tank 100 #ff0000 3.727154
Tank 100 #ff0000 70.82908
Tank 100 #ff0000 34.35118
Tank 100 #ff0000 50.94028
Tank 100 #ff0000 8.945774
Tank 100 #ff0000 8.21571
Tank 100 #ff0000 69.39197
Tank 100 #ff0000 14.36303
Tank 100 #ff0000 28.87502
Tank 100 #ff0000 64.85866
Tank 100 #ff0000 8.042771
Tank 100 #ff0000 82.21662
Tank 100 #ff0000 9.182889
Tank 200 #669900 99.31781
Tank 200 #669900 53.81911
Tank 200 #669900 31.66138
Tank 200 #669900 46.3167
Tank 200 #669900 83.92754
Tank 200 #669900 41.04061
Tank 200 #669900 36.23586
Tank 200 #669900 36.43569
Tank 200 #669900 39.58512
Tank 200 #669900 39.3236
Tank 200 #669900 27.56381
Tank 200 #669900 21.48692
Tank 200 #669900 31.75562
Tank 300 #0f0c6a 23.78412
Tank 300 #0f0c6a 56.72254
Tank 300 #0f0c6a 72.53793
Tank 300 #0f0c6a 84.15907
Tank 300 #0f0c6a 0.64275
Tank 300 #0f0c6a 94.00596
Tank 300 #0f0c6a 42.69934
Tank 300 #0f0c6a 28.84172
Tank 300 #0f0c6a 22.7959
Tank 300 #0f0c6a 95.69447
Tank 300 #0f0c6a 77.79046
Tank 300 #0f0c6a 80.76861
Tank 300 #0f0c6a 65.83209
Tank 300 #0f0c6a 77.81121
Tank 300 #0f0c6a 30.87171
Tank 300 #0f0c6a 13.10914
Tank 300 #0f0c6a 34.23243
Tank 300 #0f0c6a 35.14107
Tank 300 #0f0c6a 53.35695
Tank 300 #0f0c6a 55.39998
Tank 300 #0f0c6a 71.14835
Tank 300 #0f0c6a 73.88289
Tank 300 #0f0c6a 67.81475
Tank 300 #0f0c6a 32.29184
Tank 300 #0f0c6a 85.13162
Tank 300 #0f0c6a 13.55591
Tank 300 #0f0c6a 51.95866

 

Learn more

Create Ad Hoc Box Plots
Charts Attributes & Keywords Reference Guide
Add Custom Chart Colors
Configure Light & Dark Themes for Visual KPI Sites
Navigating Charts

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